Title page for ETD etd-05022005-113347

Monitoring Property Boundaries for the Appalachian National Scenic Trail Using Satellite Images

Degree

Master of Science

Department

Geography

Advisory Committee

Advisor Name

Title

Campbell, James B. Jr.

Committee Chair

Carstensen, Laurence William Jr.

Committee Member

Wynne, Randolph H.

Committee Member

Keywords

Property Boundary Monitoring

Vegetation Index

NDVI

Remote Sensing

Sub-Pixel Change Detection

Landsat TM

Intrusions

Encroachments

Date of Defense

2005-04-19

Availability

unrestricted

Abstract

The Appalachian National Scenic Trail is a unit of the National Park System created by the National Trails Act of 1968. Commonly referred to as the Appalachian Trail, or the AT, this National Park has some of the longest boundaries of any park. The AT is routed more than 2000 miles along the mountains of the eastern United States. The land purchased for the protection of the AT creates a separate boundary on each side of the trail. Monitoring these boundaries for intrusions or encroachments is a difficult and time-consuming task when done totally by field methods. This thesis presents a more efficient and consistent monitoring process using remote sensing data and change detection algorithms. Using Landsat TM images, Normalized Difference Vegetation Index (NDVI), and image difference change detection, this research shows that major boundary encroachments can be detected. Detection of sub-pixel vegetation index decreases identifies specific locations for field inspection. Assuming low cost multispectral Landsat imagery is available, simple NDVI difference calculation allows this technique to be applied to the entire AT one or more times per year. This procedure would improve the response time for encroachment mediation. The producer’s accuracy for finding possible encroachments was 100 percent and the consumer’s accuracy for possible encroachments indicated was 78.3 percent. Due to limited image availability, this study only examines change between one pair of Landsat images. Further refinement of these techniques should investigate other Landsat images at other times. Use of other remote sensing systems and change detection algorithms could be the focus of further research.